The scope of this paper is to estimate the production function for the Brazilian industrial sector from a longitudinal panel of the industrial sector (Annual Industrial Survey produced by the Institute of Geography and Statistics—PIA/IBGE—and the Ministry of Labour and Employment’s Annual Relation of Social Information—RAIS/MTE—ranging from 1996 until 2005) through a Bayesian Vector Autoregressive (BVAR) approach. This new method adds to the empirical industrial organization another way to estimate the demand, avoiding cumbersome calculations. It gives the possibility of analysing not only the dynamic relationships among the variables but also the shocks through the impulse response function (IRF). Additionally, it gives the opportunity to analyse the industry sector’s productivity by minimizing the problem of endogeneity and therefore it also sheds some light on the trend of this variable throughout the period abovementioned.

The main challenge of hydrogen electrolysis lies in the high cost of hydrogen production. Achieving a decarbonized energy sector requires substantial investment to shift from carbon-intensive technologies to more sustainable alternatives. However, investment decisions in this context remain complex and uncertain. Currently, green hydrogen projects account for more than 500 initiatives worldwide and are expected to expand rapidly in the coming years. Evidence from feasibility studies suggests that green hydrogen produced from renewable energy is already technically viable and is approaching economic competitiveness. The current emphasis is on large-scale deployment and learning-by-doing processes to reduce electrolyzer costs and improve supply chain efficiency. This transition requires appropriate funding mechanisms, often involving significant public sector participation alongside private investment. This study analyzes the financing structures of green hydrogen projects in Germany, Australia, and Brazil using Principal Component Analysis (PCA) to identify the most relevant combinations of technical, economic, and financial variables. Unlike previous studies that address technical, economic, and financial dimensions in isolation, this study offers an integrated, empirically grounded analysis at the project level, combining cross-country comparison with a multivariate approach. The results indicate that project characteristics are strongly associated with capital intensity and financing structures, while cost variables such as levelized cost of hydrogen (LCOH) play a secondary role in explaining variation across projects. These findings suggest that financing arrangements—particularly those involving public support mechanisms—are closely associated with project configuration in this emerging sector. However, these results should be interpreted as patterns of statistical association rather than evidence of causal relationships. Overall, the analysis highlights the importance of coordinated financing strategies in supporting the development of green hydrogen and its potential contribution to emissions reduction in line with the Paris Agreement and the transition toward climate neutrality.

If new technologies can increase production efficiency and reduce the consumption of natural resources, they can also bring new environmental risks. This dynamic is particularly relevant for the automotive industry, since it is one of the sectors that invests most in R&D, but at the same time also contributes a significant portion of greenhouse gas emissions and consumes a large amount of energy. This article aims to analyze the feasibility of meeting the environmental targets in place within 32 European countries in light of the recent technological trajectory of the automotive industry, namely with regard to the adoption of the propulsion model’s alternative to oil and diesel. Using data disaggregated by countries from 2000 up until 2020, in this paper, the estimated regressions aimed to not only verify whether electrical vehicles had a positive impact on CO₂ emissions found in the European market, but to also assess whether they will meet the target set for the next 30 years, with attention to the economy recovery after 2025 and a more robust EV market penetration in replacement of traditional fossil fuels cars.